Data Engineer

The Red Bull Athlete Performance Center serves as a dynamic accelerator for Red Bull athletes, propelling them towards unparalleled excellence in their respective sports. Leveraging advanced technology, cutting-edge analytics, and insights gleaned from a diverse array of sporting disciplines, we unlock the individual potential of each athlete.As the APC undergoes rapid expansion, both in physical infrastructure and strategic sport disciplines such as soccer, ice hockey, and Formula 1, our commitment to enhancing data infrastructure, engineering, and analytics capabilities remains unwavering. This investment underpins our mission to provide unparalleled support and resources to athletes and teams striving for greatness.In this fast-paced environment, the Data Engineer plays a pivotal role as the APC's Data Engineering lead. They are responsible for supporting heavy data-users across various departments within the APC, ensuring a reliable data pipeline that fuels decision-making and innovation. Additionally, the Data Engineer collaborates closely with high-end sports data analysts and data scientists from the global data team, spanning APC, Red Bull Soccer, and Red Bull team sports/clubs. Together, we harness the power of data to drive performance, unlock insights, and propel our athletes towards victory on the world stage.RESPONSIBILITIESAreas that play to your strengthsAll the responsibilities we'll trust you with:Design, create, maintain and scale batch and stream data pipelines to ingest data from various data sources into cloud-based data storagesTransform and model data in close alignment with data analysts and make data available to data consumers such as Data ScientistsUtilize latest technologies to work with structured and unstructured data in a highly integrated landscapeAnalyze and discuss business processes, data flows and functional/technical requirementsEvaluate, propose, and select proper application solutions and vendors in alignment with HQ ITSteer external vendors and partnersMonitor and manage corresponding IT budgetLead and support analytics projects according to the IT Project Management methodologyCollaborate with Data Science and with business to refine data requirementsTranslate the data requirements into ETL/ELT pipelines and data modelsImplement or monitor the implementation of data pipelines while ensuring a high data qualityTrain Data Scientists to integrate and use the data they need for their own use casesManage communication between business, IT partners and HQ ITAct as Service Owner for selected data & analytics applicationsDefine service strategy and roadmap in alignment with involved stakeholdersSupervise service operations and supportManage vendors, service level agreements and contractsCare for proper service definition and documentationCooperate with central service or platform ownersHigher education in Computer Science, Information Systems, Mathematics, Physics, or related quantitative field or equivalent work experience3 or more years of work experience as data engineer or software engineer with strong hands-on data skillsPractical experience working with ETL/ELT pipelines, cloud data warehouses (e.g., Snowflake, BigQuery, Redshift) and other cloud-native technologies, ideally in AWS or AzureMinimum of 3 years' experience in project managementGeneral skills/knowledge:Inter-personal contactDiplomacyConceptual workingOrganize, prioritize and coordinate multiple tasksFlexibilityAnalytical thinkingProblem solvingHands-on mentalityPerformance and result orientationPositive attitude and a strong commitment to delivering high-quality workTeam playerLanguages: fluent in German and EnglishIT related skills/knowledge:Very good skills in SQL, Python or another general-purpose language like R, C++ or JavaVery good skills working with APIs, databases, data modelling and data transformation (ideally with dbt)Solid understanding of the professional software development process following the DevOps methodology including Git, Branching Workflows, CI/CD, Containers and automated testingArchitectural knowledge related to Cloud, databases and ETL/ELTIT Project ManagementBonus:Experience with dbt and/or workflow management tools like Airflow or PrefectExperience with Infrastructure-as-Code tools like TerraformExperience with streaming technologies, such as Spark Structured Streaming, Kafka Streams or Apache FlinkFamiliarity with best practices for data architecture, data modelling, and/or data engineeringTravel 10-20%Data EngineerRed BullGiving wiiings to people and ideas since 1987In the 1980s Dietrich Mateschitz developed a formula known as the Red Bull Energy Drink. This was not only the launch of a completely new product, in fact it was the birth of a totally new product category. What drives usChasing our potentialSince the early days of Red Bull, an entrepreneurial mindset has always guided our approach to work and the environment we create: